Kai Li Division of Computer Science University of Central Florida

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Mobile Data Collection Networks for Wireless Sensor Networks *. Kai Li Division of Computer Science University of Central Florida. Traditional Wireless Sensor Networks. - PowerPoint PPT Presentation



Kai LiDivision of Computer ScienceUniversity of Central FloridaMobile Data Collection Networks for Wireless Sensor Networks*

Traditional Wireless Sensor NetworksWireless Sensor Networks are composed of a large number of small devices (irreplaceable in many applications), called wireless sensors, which are normally distributed in an ad hoc manner.Wireless sensors gather information, such as pressure, humidity, temperature, speed etc.Wireless sensors typically share some common characteristics, such as small size, low power, low cost etc.

ApplicationsMilitaryBattle damage assessment, nuclear, biological and chemical attack detection, etc.EnvironmentalForest fire detection, habitat monitoring, etc.Health applicationsPatients monitoring, drug administration, etc.IndustryProduction temperature, humidity, pressure control

Wireless Sensor NetworksInternetSink/Base StationWireless Sensor

...Data Collection in Traditional WSNsData Collection is of paramount importancesensing data needs to be routed to the sink or base-station (sometimes further transmitted over the Internet through them) for further analysis or applications.

Data transmission over the ad hoc network formed by resource-constrained sensorsdata generated at each sensor can only reach their neighbors within communication range data go through multiple sensors on their way to the sinkData Collection Issues in traditional WSNsCommunication is a major energy consumer for those energy-constrained sensorsMulti-hop communication sensors assume dual roles: data source and data forwarderFixed routing path (towards static sink) sensors in the neighborhood of the sink will deplete their energy faster (energy hole problem), which render the WSN dysfunctional prematurely

6WSNs with Mobile ElementsAdding Mobile Elements is considered to be a promising solution to the aforementioned problem. Existing approach includes

Mobile Sink Approach

Mobile Messenger Approach 7Mobile Sink ApproachMobile SinkSinks moves to different locations in the network field during WSN lifetimeSojourn for a time interval at each locationWhen sojourning at each site, routing path of sensors are updated and traffic is redirected towards the current sink siteMobile Sink ApproachAdvantagesThe neighborhood of the sink does not remain unchanged any more, thus distributing the burden of those sensors over the whole network, preventing premature cessation of network operation.LimitationsSensors still do multi-hop communicationMobile sinks are not feasible for some applications (e.g. its not possible for them to have access to Internet in harsh environments)Not scalable for large scale WSNsMobile Messenger ApproachSinkMobile MessengerSinks are staticMobile messengers start out from sink site, following a path, to visit each sensorSensors upload their data to the messenger (in a single hop ) when they approach.Mobile messengers go back to he sink to deliver the collected dataMobile Messenger ApproachAdvantages sensors transmit data in a single hop, and do not forward data for other sensorslow communication overhead w.r.t. routing energy consumption at each sensor is greatly reduced. Limitationsevery sensor has to wait a long time for the messenger to approach, thus resulting in long or even unpredictable latencylong wait may result in sensor buffer overflows, thus reducing data delivery ratioOur Approachthe MDCNetWe propose a new data collection paradigmthe Mobile Data Collection Network (MDCNet) for WSNs that featuresEnergy efficiency (single-hop communication model)Short latency (compared with mobile messenger approach)High data delivery ratio

MDCNet is a self-deployed mesh network

formed by Mobile Relay Nodes (MRNs) (e.g. mini robot, autonomous vehicles), each serving a certain number of sensors

with partial and intermittent connection among MRNs (MRN only communicate with other neighboring MRNs when it needs to transmit data)

through which data could be uploaded by sensors in a single hop and electronically transmitted towards the sink or base-stationMDCNet - A new data collection paradigmMDCNet - A new data collection paradigmA Conceptual View of MDCNet

Mobile Relay NodeSensor14MDCNet - A new data collection paradigmThe MDCNet is designed with the following three major considerations the number of sensors each MRN serves should be balanced to reduce sensor contentionsensors data should be collected in a timely manner to avoid data loss caused by sensor buffer overflowsdata relay among MRNs should conform to a reliable protocol to guarantee safe arrival at the sinkEach of the above three requirements is satisfied by corresponding techniques15Load-balanced Area PartitioningDeterministic Area Partitioning (DAP)Adaptive Search and Conquer (ASC)Local Data Collection Protocol

Data Relay ProtocolMDCNet - A new data collection paradigmLoad-balanced Area Partitioning: DAP approachAssumptionsensor locations are known a prioriCentralized administration of MRN deployment is possibleSimple partitionEvenly divide the region into several partsAssociate each partition with a mobile relay nodeMRN moves back and forth in a snake-like pattern to collect data from sensorsThe Adaptive Search and Conquer (ASC) approach has the following characteristics

It assumes no knowledge of sensor locations

No centralized deployment (i.e. decentralized self-deployment) is required

MRNs cooperatively and incrementally search and conquer different regions until the whole WSN has been coveredLoad-balanced Area Partitioning: ASC approach123L+2RL+2RLoad-balanced Area Partitioning: ASC approachThese Target Areas will be explored by other MRNs, upon their receipt of theNOTICEmessage from the MRN that claimed the bottom left region as its Service Area4th Expansion by 2R2nd Expansion by 2R3rd Expansion by 2R1st Expansion by 2RAfter conquer the area as its service area, the MRN will move in a snake-like pattern the service area to collect data from sensorsMRNs set a random timer in the beginning, the MRN whose timer expires first will be the first one to start out and at the same time send out a TIMEOUT message. Others will cancel their timer upon receipt of this message.The sensor is not served within a predefined time frame . (This is to make sure that a sensor does not get repetitive service when MRN is within its communication range )Local Data Collection Protocol

Mobile Relay Node


time4. Start sending data packet...1. HELLO message2. ACK message

If satisfy service requirement, then stop and set a wait timer3. START message5. FINISH messageCancel timer &receive dataMove& broadcasttimeoutEnd Session

Data Relay ProtocolData relay hierarchy of DAP

O(Sink Location)123654879154278663SinkData Relay ProtocolIn the ASC approach, the data relay hierarchy is automatically established as MRNs cooperatively search the sensor field. 142385679SinkO(Sink Location)12867395422Data Relay Protocol

MRN (child)time...HELP messageReady message

stop and set a wait timerstart sending data packetCancel timer &receive datastop serving & seek help

MRN (parent)FINISH messageResume serving sensorsSession endtransmit data

Serving sensorstimeoutSimulation EnvironmentSimulation Environment: NS2Network Topology: 100m by 100mSensor Nodesdata generation rate:10bit very 0.1 secondsbuffer capacity: 10KBcommunication radius: 7mrandom distributionMobile Relay Nodes:moving speed: 2m/scommunication radius: 40mPerformance MetricsData delivery ratioratio of the data packets delivered to the sink and the data packets generated by the sensorsLatencysensors average service interval by mobile relay nodesDeployment time (for ASC approach)average searching time of mobile relay nodes

Effect of Sensor DensityDAP cannot dynamically adjust the size of its service area with the increase of number of sensors (i.e. its load keep increasing) ASC tries to keep given workload (number of sensors to serve), and adjust its service area size accordingly

When there are less than 300 sensors, MRN has not reach full load. Thus, in our setting 300 is the full load point

When sensors are very sparse, the 1st MRN takes a long time to conquer a service area, which dominates the deployment timeAs sensors density increases, more MRNs are dispatched, which contributes to the gradual increase in deployment timeEffect of Load factor (ASC approach)When load factor exceeds 60, the number of partitions can not decrease any more (i.e. at least 4 parts)Taking all factors (latency, data delivery ratio, cost in terms of number of MRNs needed) into account, the optimal load factor in our setting should be between 40 to 50.

performance does not degrade anymore, because partition number has reached minimum Too many sensors per MRN. They are overloadedLatency shows rapid increase around 50, as a result of overloadConclusion and Future WorkA Mobile Data Collection Network has many advantages:Single-hop communication saves sensors energy to the largest extentElectronic transmission of sensing data over MDCNet contributes to shorter latencySelf-deployment and distributed cooperation of MRNs is fit for large scale WSNs

Future WorkFurther reduce assumptions such as location awareness (i.e. GPSs)Generalization to irregular-shaped service areasConsideration of obstacles and/or constrained path



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